The COVID-19 Situation Report is a data intensive report that tries to portray an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic. If you would like to add additional metrics to this report, please send a mail to the author at .

Date of Report

Numbers as on EOD 

## [1] "2020-05-30"

COVID-19 Overall Stats (Worldwide)

Overall Confirmed Cases Count Worldwide 

## [1] "6059017 (up from 5924275 yesterday: 2.27 % increase)"

Overall Deaths Worldwide

Please note that the deaths is at the minimum an underestimate as there could be fatalities resulting from the current active cases.

## [1] "369126 (up from 364867 yesterday: 1.17 % increase)"

Overall Fatality Rate Worldwide in %

Please note that the fatality rate is at the minimum an underestimate as there could be fatalities resulting from the current active cases.

## [1] 6.09



In- Depth Country Wise Stats (With Atleast 1000 COVID-19 Confirmations)

Overall Confirmed Cases and Deaths- Country Wise (With Fatality Rates)

Country_Region TotalConfirmed NewConfirmations CasesPercentIncrease TotalDeaths NewDeaths DeathsPercentIncrease FatalityRate
US 1770165 24146 1.38 103776 967 0.94 5.86
Brazil 498440 33274 7.15 28834 956 3.43 5.78
Russia 396575 8952 2.31 4555 181 4.14 1.15
United Kingdom 274219 1612 0.59 38458 215 0.56 14.02
Spain 239228 664 0.28 27125 4 0.01 11.34
Italy 232664 416 0.18 33340 111 0.33 14.33
France 188752 1829 0.98 28774 57 0.20 15.24
Germany 183189 267 0.15 8530 26 0.31 4.66
India 181827 8336 4.80 5185 205 4.12 2.85
Turkey 163103 983 0.61 4515 26 0.58 2.77
Peru 155671 13892 9.80 4371 272 6.64 2.81
Iran 148950 2282 1.56 7734 57 0.74 5.19
Chile 94858 4220 4.66 997 53 5.61 1.05
Canada 91681 772 0.85 7159 96 1.36 7.81
Mexico 87512 2885 3.41 9779 364 3.87 11.17
China 84128 5 0.01 4638 0 0.00 5.51
Saudi Arabia 83384 1618 1.98 480 22 4.80 0.58
Pakistan 66457 2429 3.79 1395 78 5.92 2.10
Belgium 58186 125 0.22 9453 23 0.24 16.25
Qatar 55262 2355 4.45 36 0 0.00 0.07
Netherlands 46460 132 0.28 5970 20 0.34 12.85
Bangladesh 44608 1764 4.12 610 28 4.81 1.37
Belarus 41658 894 2.19 229 5 2.23 0.55
Ecuador 38571 0 0.00 3334 0 0.00 8.64
Sweden 37113 637 1.75 4395 45 1.03 11.84
Singapore 34366 506 1.49 23 0 0.00 0.07
United Arab Emirates 33896 726 2.19 262 2 0.77 0.77
Portugal 32203 257 0.80 1396 13 0.94 4.33
South Africa 30967 1727 5.91 643 32 5.24 2.08
Switzerland 30845 17 0.06 1919 0 0.00 6.22
Colombia 26734 1328 5.23 891 36 4.21 3.33
Kuwait 26192 1008 4.00 205 11 5.67 0.78
Indonesia 25773 557 2.21 1573 53 3.49 6.10
Ireland 24929 53 0.21 1651 6 0.36 6.62
Poland 23571 416 1.80 1061 10 0.95 4.50
Egypt 23449 1367 6.19 913 34 3.87 3.89
Ukraine 23204 393 1.72 696 17 2.50 3.00
Romania 19133 151 0.80 1259 11 0.88 6.58
Philippines 17224 590 3.55 950 8 0.85 5.52
Israel 17012 25 0.15 284 0 0.00 1.67
Dominican Republic 16908 377 2.28 498 10 2.05 2.95
Japan 16716 43 0.26 894 7 0.79 5.35
Austria 16685 30 0.18 668 0 0.00 4.00
Argentina 16214 795 5.16 528 8 1.54 3.26
Afghanistan 14525 866 6.34 249 3 1.22 1.71
Panama 13018 487 3.89 330 4 1.23 2.53
Denmark 11833 40 0.34 571 3 0.53 4.83
Korea, South 11468 27 0.24 270 1 0.37 2.35
Serbia 11381 27 0.24 242 0 0.00 2.13
Bahrain 10793 344 3.29 17 2 13.33 0.16
Oman 10423 603 6.14 42 2 5.00 0.40
Kazakhstan 10382 450 4.53 38 1 2.70 0.37
Nigeria 9855 553 5.94 273 12 4.60 2.77
Bolivia 9592 861 9.86 310 10 3.33 3.23
Algeria 9267 133 1.46 646 8 1.25 6.97
Czechia 9230 34 0.37 319 0 0.00 3.46
Armenia 8927 251 2.89 127 7 5.83 1.42
Norway 8437 15 0.18 236 0 0.00 2.80
Moldova 8098 202 2.56 291 3 1.04 3.59
Morocco 7780 66 0.86 204 2 0.99 2.62
Ghana 7768 152 2.00 35 1 2.94 0.45
Malaysia 7762 30 0.39 115 0 0.00 1.48
Australia 7192 8 0.11 103 0 0.00 1.43
Finland 6826 50 0.74 316 2 0.64 4.63
Iraq 6179 306 5.21 195 10 5.41 3.16
Cameroon 5904 468 8.61 191 14 7.91 3.24
Azerbaijan 5246 257 5.15 61 3 5.17 1.16
Honduras 5094 342 7.20 201 5 2.55 3.95
Sudan 4800 279 6.17 262 29 12.45 5.46
Guatemala 4739 132 2.87 102 12 13.33 2.15
Luxembourg 4016 4 0.10 110 0 0.00 2.74
Hungary 3867 26 0.68 524 7 1.35 13.55
Tajikistan 3807 121 3.28 47 0 0.00 1.23
Guinea 3706 50 1.37 23 1 4.55 0.62
Uzbekistan 3546 78 2.25 14 0 0.00 0.39
Senegal 3535 106 3.09 42 1 2.44 1.19
Djibouti 3194 280 9.61 22 2 10.00 0.69
Thailand 3077 1 0.03 57 0 0.00 1.85
Congo (Kinshasa) 2966 133 4.69 69 0 0.00 2.33
Greece 2915 6 0.21 175 0 0.00 6.00
Cote d’Ivoire 2799 49 1.78 33 1 3.12 1.18
Gabon 2655 42 1.61 17 2 13.33 0.64
Bulgaria 2499 14 0.56 139 3 2.21 5.56
Bosnia and Herzegovina 2494 9 0.36 153 0 0.00 6.13
El Salvador 2395 117 5.14 46 4 9.52 1.92
Croatia 2246 1 0.04 103 0 0.00 4.59
North Macedonia 2164 35 1.64 131 5 3.97 6.05
Cuba 2025 20 1.00 83 1 1.22 4.10
Somalia 1916 88 4.81 73 1 1.39 3.81
Kenya 1888 143 8.19 63 1 1.61 3.34
Estonia 1865 6 0.32 67 0 0.00 3.59
Haiti 1865 281 17.74 41 6 17.14 2.20
Iceland 1806 1 0.06 10 0 0.00 0.55
Kyrgyzstan 1722 60 3.61 16 0 0.00 0.93
Maldives 1672 81 5.09 5 0 0.00 0.30
Lithuania 1670 8 0.48 70 2 2.94 4.19
Sri Lanka 1620 62 3.98 10 0 0.00 0.62
Slovakia 1521 1 0.07 28 0 0.00 1.84
New Zealand 1504 0 0.00 22 0 0.00 1.46
Slovenia 1473 0 0.00 108 0 0.00 7.33
Venezuela 1459 89 6.50 14 0 0.00 0.96
Nepal 1401 189 15.59 6 0 0.00 0.43
Equatorial Guinea 1306 0 0.00 12 0 0.00 0.92
Guinea-Bissau 1256 0 0.00 8 0 0.00 0.64
Mali 1250 24 1.96 76 3 4.11 6.08
Lebanon 1191 19 1.62 26 0 0.00 2.18
Albania 1122 23 2.09 33 0 0.00 2.94
Tunisia 1076 5 0.47 48 0 0.00 4.46
Latvia 1065 1 0.09 24 0 0.00 2.25
Kosovo 1064 16 1.53 30 0 0.00 2.82
Ethiopia 1063 95 9.81 8 0 0.00 0.75
Zambia 1057 0 0.00 7 0 0.00 0.66
Costa Rica 1047 25 2.45 10 0 0.00 0.96

In Depth USA Stats (State Wise Figures)

Confirmed Cases and Deaths- States of USA (With Fatality Rates)

State Confirmed NewConfirmations CasesPercentIncrease Deaths NewDeaths DeathsPercentIncrease FatalityRate ConfirmedCasesPerMillPopl DeathsPerMillPopl InfectionOdds
New York 369660 1376 0.37 29710 64 0.22 8.04 19002.18 1527.23 1 in 53
New Jersey 159608 764 0.48 11634 103 0.89 7.29 17969.44 1309.81 1 in 56
Illinois 118917 1462 1.24 5330 60 1.14 4.48 9384.37 420.62 1 in 107
California 109895 3273 3.07 4144 67 1.64 3.77 2781.29 104.88 1 in 360
Massachusetts 96301 789 0.83 6768 50 0.74 7.03 13857.25 973.88 1 in 72
Pennsylvania 75697 713 0.95 5537 73 1.34 7.31 5912.91 432.51 1 in 169
Texas 62675 1774 2.91 1652 33 2.04 2.64 2161.51 56.97 1 in 463
Michigan 56969 348 0.61 5464 58 1.07 9.59 5704.40 547.12 1 in 175
Florida 55424 927 1.70 2447 34 1.41 4.42 2580.53 113.93 1 in 388
Maryland 52015 1027 2.01 2509 43 1.74 4.82 8603.66 415.01 1 in 116
Georgia 46331 450 0.98 2004 17 0.86 4.33 4363.68 188.75 1 in 229
Virginia 43611 1078 2.53 1370 12 0.88 3.14 5109.36 160.51 1 in 196
Connecticut 42022 260 0.62 3912 44 1.14 9.31 11786.43 1097.25 1 in 85
Louisiana 39577 775 2.00 2786 19 0.69 7.04 8513.39 599.30 1 in 117
Ohio 35033 467 1.35 2149 18 0.84 6.13 2997.07 183.85 1 in 334
Indiana 34211 653 1.95 2125 15 0.71 6.21 5081.68 315.65 1 in 197
North Carolina 27794 909 3.38 929 10 1.09 3.34 2650.06 88.58 1 in 377
Colorado 26084 486 1.90 1443 7 0.49 5.53 4529.47 250.58 1 in 221
Minnesota 24190 659 2.80 1036 30 2.98 4.28 4289.29 183.70 1 in 233
Tennessee 22566 503 2.28 364 3 0.83 1.61 3302.42 53.27 1 in 303
Washington 21349 278 1.32 1118 7 0.63 5.24 2803.59 146.82 1 in 357
Arizona 19258 786 4.26 904 18 2.03 4.69 2528.99 118.71 1 in 395
Iowa 19244 287 1.51 531 7 1.34 2.76 6099.39 168.30 1 in 164
Wisconsin 18230 523 2.95 588 20 3.52 3.23 3130.99 100.99 1 in 319
Alabama 17359 328 1.93 618 8 1.31 3.56 3540.35 126.04 1 in 282
Mississippi 15229 436 2.95 723 13 1.83 4.75 5117.02 242.93 1 in 195
Rhode Island 14819 184 1.26 711 18 2.60 4.80 13988.62 671.16 1 in 71
Nebraska 13905 257 1.88 170 6 3.66 1.22 7188.25 87.88 1 in 139
Missouri 13298 214 1.64 774 44 6.03 5.82 2166.71 126.11 1 in 462
South Carolina 11394 263 2.36 487 4 0.83 4.27 2212.98 94.59 1 in 452
Kentucky 9704 240 2.54 431 13 3.11 4.44 2172.05 96.47 1 in 460
Kansas 9690 28 0.29 215 0 0.00 2.22 3326.11 73.80 1 in 301
Utah 9533 269 2.90 112 5 4.67 1.17 2973.53 34.93 1 in 336
Delaware 9422 186 2.01 361 5 1.40 3.83 9675.86 370.73 1 in 103
District of Columbia 8717 179 2.10 462 2 0.43 5.30 12351.42 654.62 1 in 81
Nevada 8517 141 1.68 417 11 2.71 4.90 2765.12 135.38 1 in 362
New Mexico 7624 131 1.75 351 7 2.03 4.60 3635.97 167.40 1 in 275
Arkansas 7013 236 3.48 133 1 0.76 1.90 2323.86 44.07 1 in 430
Oklahoma 6418 80 1.26 334 5 1.52 5.20 1621.95 84.41 1 in 617
South Dakota 4960 94 1.93 62 3 5.08 1.25 5606.68 70.08 1 in 178
New Hampshire 4492 0 0.00 238 0 0.00 5.30 3303.64 175.04 1 in 303
Oregon 4185 54 1.31 153 2 1.32 3.66 992.24 36.28 1 in 1008
Puerto Rico 3718 71 1.95 133 1 0.76 3.58 1164.17 41.64 1 in 859
Idaho 2803 33 1.19 82 0 0.00 2.93 1564.12 45.76 1 in 639
North Dakota 2554 34 1.35 60 1 1.69 2.35 3351.43 78.73 1 in 298
Maine 2282 56 2.52 89 4 4.71 3.90 1697.65 66.21 1 in 589
West Virginia 1989 38 1.95 75 1 1.35 3.77 1112.95 41.97 1 in 899
Vermont 977 2 0.21 55 0 0.00 5.63 1565.73 88.14 1 in 639
Wyoming 898 7 0.79 16 1 6.67 1.78 1551.60 27.65 1 in 644
Hawaii 651 2 0.31 17 0 0.00 2.61 459.79 12.01 1 in 2175
Montana 505 12 2.43 17 0 0.00 3.37 472.50 15.91 1 in 2116
Alaska 433 4 0.93 10 0 0.00 2.31 591.90 13.67 1 in 1689

US Tested- Confirmed Funnel (All States)

State Level Figures

State Tested Confirmed ConfirmationRate TestsPerMillPopl
New York 2005381 369660 18.43 103085.55
New Jersey 745308 159608 21.42 83910.39
Illinois 877105 118917 13.56 69216.97
California 1888595 109895 5.82 47797.74
Massachusetts 582519 96301 16.53 83821.68
Pennsylvania 447772 75697 16.91 34976.75
Texas 893275 62675 7.02 30806.96
Michigan 538812 56969 10.57 53952.11
Florida 994968 55424 5.57 46325.55
Maryland 293946 52015 17.70 48620.83
Georgia 454838 46331 10.19 42838.83
Virginia 305512 43611 14.27 35793.02
Connecticut 246935 42022 17.02 69260.90
Louisiana 368819 39577 10.73 79336.49
Ohio 381947 35033 9.17 32675.48
Indiana 256395 34211 13.34 38084.77
North Carolina 404157 27794 6.88 38534.87
Colorado 175741 26084 14.84 30517.29
Minnesota 242508 24190 9.97 43000.68
Tennessee 427046 22566 5.28 62495.99
Washington 348233 21349 6.13 45730.52
Arizona 217047 19258 8.87 28502.96
Iowa 150423 19244 12.79 47676.60
Wisconsin 261138 18230 6.98 44850.32
Alabama 212201 17359 8.18 43278.20
Mississippi 165932 15229 9.18 55753.93
Rhode Island 150317 14819 9.86 141894.03
Nebraska 99008 13905 14.04 51182.58
Missouri 185430 13298 7.17 30212.98
South Carolina 189519 11394 6.01 36809.00
Kentucky 208195 9704 4.66 46600.32
Kansas 94949 9690 10.21 32591.41
Utah 210105 9533 4.54 65535.79
Delaware 59329 9422 15.88 60927.49
District of Columbia 45629 8717 19.10 64653.30
Nevada 138532 8517 6.15 44975.64
New Mexico 188261 7624 4.05 89783.67
Arkansas 126497 7013 5.54 41916.61
Oklahoma 193118 6418 3.32 48804.50
South Dakota 42938 4960 11.55 48536.22
New Hampshire 68960 4492 6.51 50716.66
Oregon 126795 4185 3.30 30062.33
Puerto Rico 3718 3718 100.00 1164.17
Idaho 45424 2803 6.17 25347.29
North Dakota 70981 2554 3.60 93143.34
Maine 49566 2282 4.60 36873.65
West Virginia 95890 1989 2.07 53655.35
Vermont 32667 977 2.99 52351.88
Wyoming 24083 898 3.73 41611.45
Hawaii 54014 651 1.21 38148.93
Montana 39284 505 1.29 36756.00
Alaska 51695 433 0.84 70665.51

In Depth India Stats (State Wise Figures)

Confirmed Cases and Deaths (States of India)

State Confirmed NewConfirmations CasesPercentIncrease Recovered RecoveryRate Active Deaths NewDeaths DeathsPercentIncrease FatalityRate
Maharashtra 65168 2940 4.72 28081 43.09 34890 2197 99 4.72 3.37
Tamil Nadu 21184 938 4.63 12000 56.65 9021 163 6 3.82 0.77
Delhi 18549 1163 6.69 8075 43.53 10058 416 18 4.52 2.24
Gujarat 16356 412 2.58 9232 56.44 6117 1007 27 2.76 6.16
Rajasthan 8617 252 3.01 5739 66.60 2685 193 9 4.89 2.24
Madhya Pradesh 7891 246 3.22 4444 56.32 3104 343 9 2.69 4.35
Uttar Pradesh 7701 256 3.44 4651 60.39 2837 213 12 5.97 2.77
State Unassigned 5491 818 17.50 0 0.00 5491 0 0 NaN 0.00
West Bengal 5130 317 6.59 1970 38.40 2851 309 7 2.32 6.02
Bihar 3565 206 6.13 1311 36.77 2233 21 6 40.00 0.59
Andhra Pradesh 3461 131 3.93 2289 66.14 1112 60 0 0.00 1.73
Karnataka 2922 141 5.07 997 34.12 1874 49 1 2.08 1.68
Telangana 2499 74 3.05 1412 56.50 1010 77 6 8.45 3.08
Jammu and Kashmir 2341 177 8.18 908 38.79 1405 28 0 0.00 1.20
Punjab 2233 36 1.64 1967 88.09 222 44 2 4.76 1.97
Haryana 1923 202 11.74 971 50.49 932 20 1 5.26 1.04
Odisha 1819 96 5.57 1050 57.72 760 9 0 0.00 0.49
Assam 1217 159 15.03 164 13.48 1046 4 0 0.00 0.33
Kerala 1209 58 5.04 575 47.56 624 10 1 11.11 0.83
Uttarakhand 749 33 4.61 102 13.62 639 5 1 25.00 0.67
Jharkhand 563 42 8.06 256 45.47 302 5 0 0.00 0.89
Chhattisgarh 447 32 7.71 102 22.82 344 1 0 0.00 0.22
Himachal Pradesh 313 18 6.10 107 34.19 197 6 0 0.00 1.92
Chandigarh 289 0 0.00 199 68.86 86 4 0 0.00 1.38
Tripura 271 17 6.69 172 63.47 99 0 0 NaN 0.00
Ladakh 77 3 4.05 43 55.84 34 0 0 NaN 0.00
Goa 70 1 1.45 42 60.00 28 0 0 NaN 0.00
Manipur 60 1 1.69 6 10.00 54 0 0 NaN 0.00
Puducherry 57 4 7.55 23 40.35 34 0 0 NaN 0.00
Nagaland 36 11 44.00 0 0.00 36 0 0 NaN 0.00
Andaman and Nicobar Islands 33 0 0.00 33 100.00 0 0 0 NaN 0.00
Meghalaya 27 0 0.00 12 44.44 14 1 0 0.00 3.70
Arunachal Pradesh 3 0 0.00 1 33.33 2 0 0 NaN 0.00
Dadra and Nagar Haveli and Daman and Diu 2 0 0.00 1 50.00 1 0 0 NaN 0.00
Mizoram 1 0 0.00 1 100.00 0 0 0 NaN 0.00
Sikkim 1 0 0.00 0 0.00 1 0 0 NaN 0.00
Lakshadweep 0 0 NaN 0 NaN 0 0 0 NaN NaN

In Depth Italy Stats (Region Wise Figures)

Confirmed Cases and Deaths- Regions of Italy (With Fatality and Confirmation Rates)

Region Swabs Confirmations NewConfirmations CasesPercentIncrease ConfirmationRate HospitalizedWithSymptoms IntensiveCare ActiveCases Deceased FatalityRate
Lombardia 741447 88758 221 0.25 11.97 3307 172 21809 16079 18.12
Piemonte 315828 30583 82 0.27 9.68 988 60 5290 3858 12.61
Emilia-Romagna 321373 27759 20 0.07 8.64 398 65 3279 4107 14.80
Veneto 660151 19146 12 0.06 2.90 120 7 1612 1916 10.01
Toscana 249441 10100 12 0.12 4.05 106 27 1166 1037 10.27
Liguria 104892 9651 32 0.33 9.20 186 9 781 1459 15.12
Lazio 253388 7715 6 0.08 3.04 769 58 3055 728 9.44
Marche 102484 6727 4 0.06 6.56 66 9 1347 987 14.67
Campania 198033 4797 10 0.21 2.42 236 7 981 411 8.57
Puglia 116765 4490 8 0.18 3.85 150 12 1222 500 11.14
P.A. Trento 86565 4429 1 0.02 5.12 13 3 366 462 10.43
Sicilia 148871 3442 2 0.06 2.31 67 7 999 273 7.93
Friuli Venezia Giulia 131976 3271 4 0.12 2.48 45 1 305 333 10.18
Abruzzo 73301 3237 0 0.00 4.42 122 3 770 404 12.48
P.A. Bolzano 65405 2596 1 0.04 3.97 13 4 137 291 11.21
Umbria 70023 1431 0 0.00 2.04 16 1 31 76 5.31
Sardegna 56580 1356 0 0.00 2.40 34 2 186 130 9.59
Valle d’Aosta 14972 1183 1 0.08 7.90 13 0 17 143 12.09
Calabria 69334 1158 0 0.00 1.67 23 1 151 97 8.38
Molise 14371 436 0 0.00 3.03 3 2 156 22 5.05
Basilicata 29421 399 0 0.00 1.36 5 0 31 27 6.77

In Depth Canada Stats (With Province Level Figures)

Confirmed Cases and Deaths- Provinces of Canada (With Fatality Rates)

Province Confirmed NewConfirmations CasesPercentIncrease Deaths NewDeaths DeathsPercentIncrease FatalityRate ConfirmedCasesPerMillPopl DeathsPerMillPopl InfectionOdds
Quebec 50651 419 0.83 4439 76 1.74 8.76 5932.65 519.93 1 in 169
Ontario 29023 323 1.13 2332 19 0.82 8.04 1972.77 158.51 1 in 507
Alberta 6992 13 0.19 143 0 0.00 2.05 1584.36 32.40 1 in 631
British Columbia 2573 11 0.43 164 0 0.00 6.37 503.43 32.09 1 in 1986
Nova Scotia 1056 1 0.09 60 1 1.69 5.68 1080.35 61.38 1 in 926
Saskatchewan 645 4 0.62 10 0 0.00 1.55 545.84 8.46 1 in 1832
Manitoba 294 0 0.00 7 0 0.00 2.38 213.43 5.08 1 in 4685
Newfoundland and Labrador 261 0 0.00 3 0 0.00 1.15 500.61 5.75 1 in 1998
New Brunswick 129 1 0.78 0 0 NaN 0.00 165.39 0.00 1 in 6046
Prince Edward Island 27 0 0.00 0 0 NaN 0.00 170.72 0.00 1 in 5858
Yukon 11 0 0.00 0 0 NaN 0.00 267.78 0.00 1 in 3734
Northwest Territories 5 0 0.00 0 0 NaN 0.00 111.35 0.00 1 in 8981

In Depth China Stats (With Province Level Figures)

Confirmed Cases and Deaths- Provinces of China (With Fatality Rates)

Province Confirmed Deaths FatalityRate
Hubei 68135 4512 6.62
Guangdong 1593 8 0.50
Henan 1276 22 1.72
Zhejiang 1268 1 0.08
Hong Kong 1082 4 0.37
Hunan 1019 4 0.39
Anhui 991 6 0.61
Heilongjiang 945 13 1.38
Jiangxi 937 1 0.11
Shandong 792 7 0.88
Shanghai 672 7 1.04
Jiangsu 653 0 0.00
Beijing 593 9 1.52
Chongqing 579 6 1.04
Sichuan 564 3 0.53
Fujian 358 1 0.28
Hebei 328 6 1.83
Shaanxi 308 3 0.97
Guangxi 254 2 0.79
Inner Mongolia 232 1 0.43
Shanxi 198 0 0.00
Tianjin 192 3 1.56
Yunnan 185 2 1.08
Hainan 169 6 3.55
Jilin 155 2 1.29
Liaoning 149 2 1.34
Guizhou 147 2 1.36
Gansu 139 2 1.44
Xinjiang 76 3 3.95
Ningxia 75 0 0.00
Macau 45 0 0.00
Qinghai 18 0 0.00
Tibet 1 0 0.00

Time Series Curves (Top 20 Countries with the Highest Cases)

The time series curves (both linear and logarithmic) are printed for the top 20 countries with the most confirmed COVID-19 cases as of today in decreasing order of confirmations.

Confirmed Cases Count (Linear)

Country Wise Time Series Curve

Confirmed Cases Count (Logarithmic)

Country Wise Time Series Curve

Time Series Curves (Top 20 Countries with the Highest Deaths)

The time series curves (both linear and logarithmic) are printed for the top 20 countries with the most COVID-19 deaths as of today in decreasing order of confirmations.

Death Count (Linear)

Country Wise Time Series Curve

Death Count (Logarithmic)

Country Wise Time Series Curve

Epidemic Curve: Delta in the past 24 hrs (Top 20 Countries with the Highest Cases)

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in various countries. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The below charts show if this has happened for the worst affected 20 countries in the world as of today. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Delta in Confirmed Cases

Number of New Cases in the past 24 hrs

Delta in Deaths

Number of Deaths in the past 24 hrs

Measuring Outbreak Velocity: 5 Day Lagging Average Doubling Time (Top 20 Countries with the Highest Cases)

The velocity of an outbreak is determined by a construct known as doubling time. This value describes the number of days, on average, required for the number of cases to double in a given area. For our analysis we use average doubling time, which can be defined as the number of days, on average, required for the average number of COVID-19 cases to double in a given area.

This measure can describe COVID-19 behavior worldwide, in a country, or even in a smaller region such as a state. For our analysis, we will discuss average doubling time at a national level for the top 20 most affected countries.

Below, we have calculated average doubling time for several nations, on a trailing, rolling 5-day basisbased on today’s case values. A decline in average doubling time indicates that the COVID-19 outbreak (confirmation rate) is accelerating (average cases double in fewer days), while an increase of average doubling time indicates that the outbreak is slowing.

Ideally, when social distancing and lockdowns are implemented aggressively in a country and after some period of delay, doubling times should begin to increase in a matter of days, weeks, or months, depending upon the severity of the epidemic and the degree of social distancing achievable.

Given the fact that many countries across the world have already enacted or implemented social distancing measures, this is why one should be cautious not to extrapolate COVID-19 growth rates from trailing statistics.

5 Day Lagging Avg Doubling Time of Confirmations

Confirmed Cases and Deaths Per Million Population and Infection Odds

This metric confirmed cases per million population and deaths per million population shows the extent to which the disease has spread with respect to the population of the country. The metric Infection Odds shows 1 in how many people are infected with COVID-19 in the corresponding country.

For the top 20 countries with most confirmed cases excluding cruise ships

Country_Region ConfirmedCasesPerMillionPopl DeathsPerMillionPopl InfectionOdds
US 5410.04 317.16 1 in 185
Brazil 2381.46 137.76 1 in 420
Russia 2744.46 31.52 1 in 364
United Kingdom 4127.32 578.84 1 in 242
Spain 5127.05 581.33 1 in 195
Italy 3846.96 551.26 1 in 260
France 2817.61 429.53 1 in 355
Germany 2212.69 103.03 1 in 452
India 135.79 3.87 1 in 7364
Turkey 2018.35 55.87 1 in 495
Peru 4839.01 135.87 1 in 207
Iran 1835.26 95.29 1 in 545
Chile 5255.29 55.24 1 in 190
Canada 2438.97 190.45 1 in 410
Mexico 677.34 75.69 1 in 1476
China 60.70 3.35 1 in 16475
Saudi Arabia 2531.39 14.57 1 in 395
Pakistan 337.35 7.08 1 in 2964
Belgium 5104.04 829.21 1 in 196
Qatar 20940.51 13.64 1 in 48

US Detailed State and County Level Curves

This section of the report might be of interest to people who want an an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic at the state/ county level in USA.

Epidemic Curve: Delta in Confirmed Cases in US States

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in various US states. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The below charts show if this has happened for the worst affected 20 states in USA as of today. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Number of New Cases in the past 24 hrs

Epidermic Curve: Delta in Deaths in US States

Number of Deaths in the past 24 hrs

Top 50 US Counties with the Highest Cases and Deaths

All NYC boroughs are mentioned together as New York County

County State Confirmations Deaths FatalityRate
New York New York 202751 21512 10.61
Cook Illinois 77119 3603 4.67
Los Angeles California 53746 2339 4.35
Nassau New York 40307 2121 5.26
Suffolk New York 39532 1892 4.79
Westchester New York 33429 1364 4.08
Philadelphia Pennsylvania 22629 1308 5.78
Middlesex Massachusetts 21124 1596 7.56
Wayne Michigan 20254 2452 12.11
Hudson New Jersey 18919 1173 6.20
Bergen New Jersey 18211 1573 8.64
Suffolk Massachusetts 17873 868 4.86
Miami-Dade Florida 17826 700 3.93
Essex New Jersey 17594 1657 9.42
Passaic New Jersey 16099 925 5.75
Middlesex New Jersey 15824 989 6.25
Union New Jersey 15764 1067 6.77
Fairfield Connecticut 15502 1267 8.17
Prince George’s Maryland 15022 539 3.59
Essex Massachusetts 14099 909 6.45
Rockland New York 13128 631 4.81
Harris Texas 12220 231 1.89
New Haven Connecticut 11309 966 8.54
Montgomery Maryland 11251 605 5.38
Providence Rhode Island 11052 0 0.00
Fairfax Virginia 10906 383 3.51
Worcester Massachusetts 10901 753 6.91
Orange New York 10389 444 4.27
Hartford Connecticut 10207 1238 12.13
Dallas Texas 9787 223 2.28
Marion Indiana 9761 576 5.90
Maricopa Arizona 9522 430 4.52
District of Columbia District of Columbia 8717 462 5.30
Ocean New Jersey 8700 726 8.34
Oakland Michigan 8319 983 11.82
Lake Illinois 8238 288 3.50
Hennepin Minnesota 8181 606 7.41
Monmouth New Jersey 8159 596 7.30
Norfolk Massachusetts 8016 815 10.17
King Washington 7993 567 7.09
Plymouth Massachusetts 7819 548 7.01
Milwaukee Wisconsin 7656 299 3.91
DuPage Illinois 7620 368 4.83
Jefferson Louisiana 7536 447 5.93
Riverside California 7486 323 4.31
San Diego California 7385 269 3.64
Orleans Louisiana 7108 507 7.13
Bristol Massachusetts 7089 410 5.78
Broward Florida 7067 313 4.43
Montgomery Pennsylvania 7006 682 9.73

Overall US Choropleth Map

Choropleths are an ideal way to visualize the past/ current COVID-19 hotspots within a country. The below are the hotspots in the US.

County level COVID-19 Confirmations Map

Canada Detailed Province Level Curves

This section of the report might be of interest to people who want an an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic at the province level in Canada.

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in the most affected Canadian provinces- Quebec, Ontario, Alberta and British Columbia. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Epidemic Curve: Delta in Confirmed Cases in Canadian Provinces

Number of New Cases in the past 24 hrs

Epidermic Curve: Delta in Deaths in Canadian Provinces

Number of Deaths in the past 24 hrs

Data Sources

CSSEGISandData, The NY Times, amodm/api-covid19-in and pcm-dpc